Collagen Biomarkers for Arthritis Applications

The most common form of chronic arthritis is osteoarthritis (OA) with prevalence as high as 80% after age 75 (Arden and Nevitt, 2006). The incidence of OA is expected to increase as the population ages, increasing the socioeconomic burden of OA. Despite the signifi cant burden of this disease, no drug has been identifi ed that can effectively modify disease progression (Moskowitz and Hooper, 2005; Abadie et al. 2004). However, slowing disease progress and improvement in quality of life may be achieved by behavioral modifi cations, such as weight loss and exercise. Many patients with early OA will progress to disability and joint replacement. Physical examination and radiographic studies are relatively poor means for detecting disease early or predicting progression. Therefore, identifi cation of factors to facilitate early OA diagnosis and prognosis is a major focus of current OA research (Lohmander and Felson, 2004; Lohmander, 2004; Garnero and Delmas, 2003)

Changes in serum and synovial fluid biomarkers after acute injury (NCT00332254)

INTRODUCTION: Acute trauma involving the anterior cruciate ligament is believed to be a major risk factor for the development of post-traumatic osteoarthritis 10 to 20 years post-injury. In this study, to better understand the early biological changes which occur after acute injury, we investigated synovial fluid and serum biomarkers. METHODS: We collected serum from 11 patients without pre-existing osteoarthritis from a pilot intervention trial (5 placebo and 6 drug treated) using an intra-articular interleukin-1 receptor antagonist (IL-1Ra) therapy, 9 of which also supplied matched synovial fluid samples at presentation to the clinic after acute knee injury (mean 15.2 ± 7.2 days) and at the follow-up visit for reconstructive surgery (mean 47.6 ± 12.4 days). To exclude patients with pre-existing osteoarthritis (OA), the study was limited to individuals younger than 40 years of age (mean 23 ± 3.5) with no prior history of joint symptoms or trauma. We profiled a total of 21 biomarkers; 20 biomarkers in synovial fluid and 13 in serum with 12 biomarkers measured in both fluids. Biomarkers analyzed in this study were found to be independent of treatment (P > 0.05) as measured by Mann-Whitney and two-way ANOVA. RESULTS: We observed significant decreases in synovial fluid (sf) biomarker concentrations from baseline to follow-up for (sf)C-Reactive protein (CRP) (P = 0.039), (sf)lubricin (P = 0.008) and the proteoglycan biomarkers: (sf)Glycosaminoglycan (GAG) (P = 0.019), and (sf)Alanine-Arginine-Glycine-Serine (ARGS) aggrecan (P = 0.004). In contrast, we observed significant increases in the collagen biomarkers: (sf)C-terminal crosslinked telopeptide type II collagen (CTxII) (P = 0.012), (sf)C1,2C (P = 0.039), (sf)C-terminal crosslinked telopeptide type I collagen (CTxI) (P = 0.004), and (sf)N-terminal telopeptides of type I collagen (NTx) (P = 0.008). The concentrations of seven biomarkers were significantly higher in synovial fluid than serum suggesting release from the signal knee: IL-1β (P < 0.0001), fetal aggrecan FA846 (P = 0.0001), CTxI (P = 0.0002), NTx (P = 0.012), osteocalcin (P = 0.012), Cartilage oligomeric matrix protein (COMP) (P = 0.0001) and matrix metalloproteinase (MMP)-3 (P = 0.0001). For these seven biomarkers we found significant correlations between the serum and synovial fluid concentrations for only CTxI (P = 0.0002), NTx (P < 0.0001), osteocalcin (P = 0.0002) and MMP-3 (P = 0.038). CONCLUSIONS: These data strongly suggest that the biology after acute injury reflects that seen in cartilage explant models stimulated with pro-inflammatory cytokines, which are characterized by an initial wave of proteoglycan loss followed by subsequent collagen loss. As the rise of collagen biomarkers in synovial fluid occurs within the first month after injury, and as collagen loss is thought to be irreversible, very early treatment with agents to either reduce inflammation and/or reduce collagen loss may have the potential to reduce the onset of future post-traumatic osteoarthritis. TRIAL REGISTRATION: The samples used in this study were derived from a clinical trial NCT00332254 registered with ClinicalTrial.gov

Post-translational aging of proteins in osteoarthritic cartilage and synovial fluid as measured by isomerized aspartate

INTRODUCTION: Aging proteins undergo non-enzymatic post-translational modification, including isomerization and racemization. We hypothesized that cartilage with many long-lived components could accumulate non-enzymatically modified amino acids in the form of isomerized aspartate and that its liberation due to osteoarthritis (OA)-related cartilage degradation could reflect OA severity. METHODS: Articular cartilage and synovial fluid were obtained from 14 randomly selected total knee arthroplasty cases (56 to 79 years old) and non-arthritis cartilage from 8 trauma cases (51 to 83 years old). Paired lesional cartilage and non-lesioned OA cartilage were graded histologically using a modified Mankin system. Paired cartilage and synovial fluids were assayed for isomerized aspartate, phosphate-buffered saline/EDTA (ethylenediaminetetraacetic acid) extractable glycosaminoglycans, and total protein. Macroscopically normal non-lesioned OA cartilage was separated into superficial and deep regions when cartilage thickness was at least 3 mm (n = 6). RESULTS: Normalized to cartilage wet weight, normal cartilage and deep non-lesioned OA cartilage contained significantly (P < 0.05) more isomerized aspartate than superficial non-lesioned OA cartilage and lesioned cartilage. Synovial fluid isomerized aspartate correlated positively (R2 = 0.53, P = 0.02) and glycosaminoglycans correlated negatively (R2 = 0.42, P = 0.04) with histological OA lesion severity. Neither synovial fluid isomerized aspartate nor glycosaminoglycans nor total protein correlated with histological scores of non-lesioned areas. CONCLUSIONS: We show for the first time that human cartilage and synovial fluid contain measurable quantities of an isomerized amino acid and that synovial fluid concentrations of isomerized aspartate reflected severity of histological OA. Further assessment is warranted to identify the cartilage proteins containing this modification and to assess the functional consequences and biomarker applications of this analyte in OA

Patellar Skin Surface Temperature by Thermography Reflects Knee Osteoarthritis Severity

BACKGROUND: Digital infrared thermal imaging is a means of measuring the heat radiated from the skin surface. Our goal was to develop and assess the reproducibility of serial infrared measurements of the knee and to assess the association of knee temperature by region of interest with radiographic severity of knee Osteoarthritis (rOA). METHODS: A total of 30 women (15 Cases with symptomatic knee OA and 15 age-matched Controls without knee pain or knee OA) participated in this study. Infrared imaging was performed with a Meditherm Med2000™ Pro infrared camera. The reproducibility of infrared imaging of the knee was evaluated through determination of intraclass correlation coefficients (ICCs) for temperature measurements from two images performed 6 months apart in Controls whose knee status was not expected to change. The average cutaneous temperature for each of five knee regions of interest was extracted using WinTes software. Knee x-rays were scored for severity of rOA based on the global Kellgren-Lawrence grading scale. RESULTS: The knee infrared thermal imaging procedure used here demonstrated long-term reproducibility with high ICCs (0.50-0.72 for the various regions of interest) in Controls. Cutaneous temperature of the patella (knee cap) yielded a significant correlation with severity of knee rOA (R = 0.594, P = 0.02). CONCLUSION: The skin temperature of the patellar region correlated with x-ray severity of knee OA. This method of infrared knee imaging is reliable and as an objective measure of a sign of inflammation, temperature, indicates an interrelationship of inflammation and structural knee rOA damage

First Qualification Study of Serum Biomarkers as Indicators of Total Body Burden of Osteoarthritis

BACKGROUND: Osteoarthritis (OA) is a debilitating chronic multijoint disease of global proportions. OA presence and severity is usually documented by x-ray imaging but whole body imaging is impractical due to radiation exposure, time and cost. Systemic (serum or urine) biomarkers offer a potential alternative method of quantifying total body burden of disease but no OA-related biomarker has ever been stringently qualified to determine the feasibility of this approach. The goal of this study was to evaluate the ability of three OA-related biomarkers to predict various forms or subspecies of OA and total body burden of disease. METHODOLOGY/PRINCIPAL FINDINGS: Female participants (461) with clinical hand OA underwent radiography of hands, hips, knees and lumbar spine; x-rays were comprehensively scored for OA features of osteophyte and joint space narrowing. Three OA-related biomarkers, serum hyaluronan (sHA), cartilage oligomeric matrix protein (sCOMP), and urinary C-telopeptide of type II collagen (uCTX2), were measured by ELISA. sHA, sCOMP and uCTX2 correlated positively with total osteophyte burden in models accounting for demographics (age, weight, height): R(2) = 0.60, R(2) = 0.47, R(2) = 0.51 (all p<10(-6)); sCOMP correlated negatively with total joint space narrowing burden: R(2) = 0.69 (p<10(-6)). Biomarkers and demographics predicted 35-38% of variance in total burden of OA (total joint space narrowing or osteophyte). Joint size did not determine the contribution to the systemic biomarker concentration. Biomarker correlation with disease in the lumbar spine resembled that in the rest of the skeleton. CONCLUSIONS/SIGNIFICANCE: We have suspected that the correlation of systemic biomarkers with disease has been hampered by the inability to fully phenotype the burden of OA in a patient. These results confirm the hypothesis, revealed upon adequate patient phenotyping, that systemic joint tissue concentrations of several biomarkers can be quantitative indicators of specific subspecies of OA and of total body burden of disease

Serum N-propeptide of collagen IIA (PIIANP) as a marker of radiographic osteoarthritis burden

Cartilage homeostasis relies on a balance of catabolism and anabolism of cartilage matrix. Our goal was to evaluate the burden of radiographic osteoarthritis and serum levels of type IIA procollagen amino terminal propeptide (sPIIANP), a biomarker representing type II collagen synthesis, in osteoarthritis

Dietary Diversity Was Positively Associated with Psychological Resilience among Elders: A Population-Based Study

The association between dietary diversity (DD) and psychological resilience among older people is an underdeveloped area of research. This cross-sectional study explored the associations of DD with psychological resilience among 8571 community-based elderly individuals. The intake frequencies of food groups were collected, and dietary diversity was assessed based on the mean DD score. Psychological resilience was assessed using a simplified resilience score (SRS). Data were analyzed using multiple linear regression and logistic regression models. Poor DD was significantly associated with psychological resilience, with a β (95% CI) of −0.94 (−1.07, −0.81) for the SRS (p \u3c 0.01) and an odds ratio (95% CI) of 1.83 (1.66, 2.01) for low SRS status. The interaction effects of age with DD were observed for the SRS (p \u3c 0.001) and low SRS status (p \u3c 0.001). Based on separate analyses by age group, the association of a low SRS with poor DD was more prominent in the younger elderly than the oldest old, with OR (95% CI) 2.32 (1.96, 2.74) and 1.61 (1.43, 1.82), respectively. Compared with younger participants with good DD, the risk of a low SRS was greater for younger participants with poor DD, the oldest old with good DD, and the oldest old with poor DD, with OR (95% CI) 2.39 (2.02, 2.81), 1.28 (1.09, 1.51), and 2.03 (1.72, 2.39), respectively. The greatest contribution to DD was from a high consumption of vegetables, fruits, and nuts. Our study suggested that poor DD was associated with a low psychological resilience among the Chinese elderly, especially the younger elderly. These findings suggest that augmentation of DD might promote psychological resilience

Quantification of the whole-body burden of radiographic osteoarthritis using factor analysis

INTRODUCTION: Although osteoarthritis (OA) commonly involves multiple joints, no widely accepted method for quantifying whole-body OA burden exists. Therefore, our aim was to apply factor analytic methods to radiographic OA (rOA) grades across multiple joint sites, representing both presence and severity, to quantify the burden of rOA. METHODS: We used cross-sectional data from the Johnston County Osteoarthritis Project. The sample (n = 2092) had a mean age of 65 ± 11 years, body mass index (BMI) 31 ± 7 kg/m2, with 33% men and 34% African Americans. A single expert reader (intra-rater κ = 0.89) provided radiographic grades based on standard atlases for the hands (30 joints, including bilateral distal and proximal interphalangeal [IP], thumb IP, metacarpophalangeal [MCP] and carpometacarpal [CMC] joints), knees (patellofemoral and tibiofemoral, 4 joints), hips (2 joints), and spine (5 levels [L1/2 to L5/S1]). All grades were entered into an exploratory common factor analysis as continuous variables. Stratified factor analyses were used to look for differences by gender, race, age, and cohort subgroups. RESULTS: Four factors were identified as follows: IP/CMC factor (20 joints), MCP factor (8 joints), Knee factor (4 joints), Spine factor (5 levels). These factors had high internal consistency reliability (Cronbach's α range 0.80 to 0.95), were not collapsible into a single factor, and had moderate between-factor correlations (Pearson correlation coefficient r = 0.24 to 0.44). There were no major differences in factor structure when stratified by subgroup. CONCLUSIONS: The 4 factors obtained in this analysis indicate that the variables contained within each factor share an underlying cause, but the 4 factors are distinct, suggesting that combining these joint sites into one overall measure is not appropriate. Using such factors to reflect multi-joint rOA in statistical models can reduce the number of variables needed and increase precision